Identifying markers associated with it components in an image

ABSTRACT

Described are methods, systems, and apparatus, including computer program products for locating one or more markers associated with IT equipment. An image of a scene including the one or more markers is acquired by a mobile computing device. A band-pass filter is applied by the mobile computing device to first pixel data associated with a first pixel in the image to generate a first band-pass filter result, wherein a pass-band of the band-pass filter is based on the light emitted by the one or more markers. A first pixel score is determined by the mobile computing device based on at least the first band-pass filter result. First indicia of the first pixel score is stored by the mobile computing device in a map at a first map location corresponding to a first image location of the first pixel in the image.

TECHNOLOGICAL FIELD

The present technology relates generally to identifying markers in animage, and more specifically to identifying markers associated with ITequipment in an image based on light emitted by the markers.

BACKGROUND

A data center can include various physical resources to support andprovide, e.g., computer processing and/or storage. A data center caninclude IT components, such as racks, servers, data storage devices,disk drives, networking equipment, and uninterruptible power supplies(UPSs). Data centers can include supporting resources, such as HVACunits, chillers, cooling equipment, generators, and battery backupsystems. In some cases, the physical resources of a data center can behoused in an enclosure, such as a room or building. For a large-scaleservice, a data center can require a large number of physical resourcesoccupying one or more buildings.

There have been recent developments in mobile computing devices such aslaptops, smart phones, and tablets. In particular, mobile computingdevices can provide a variety of functions such as a digital camera.

SUMMARY

As the number of the IT components in data centers increase, themanagement of the data centers becomes increasingly complex.Accordingly, there is a need to simplify the management of data centers.As described herein, mobile computing devices can be used to identify ITcomponents, thereby facilitating management.

In one aspect, there is a method executed on a mobile computing devicefor locating one or more markers associated with IT equipment. Themethod can include acquiring, by the mobile computing device, an imageof a scene including the one or more markers. The method can includeapplying, by the mobile computing device, a band-pass filter to firstpixel data associated with a first pixel in the image to generate afirst band-pass filter result, wherein a pass-band of the band-passfilter is based on the light emitted by the one or more markers. Themethod can include determining, by the mobile computing device, a firstpixel score based on at least the first band-pass filter result. Themethod can include storing, by the mobile computing device, in a mapfirst indicia of the first pixel score at a first map locationcorresponding to a first image location of the first pixel in the image.

In some embodiments, the method can include applying, by the mobilecomputing device, the band-pass filter to second pixel data associatedwith a second pixel in the image to generate a second band-pass filterresult. The method can include determining, by the mobile computingdevice, a second pixel score based on at least the second band-passfilter result. The method can include storing, by the mobile computingdevice, in the map second indicia of the second pixel score at a secondmap location corresponding to a second image location of the secondpixel in the image.

In some embodiments, the method can include applying the band-passfilter to a hue value of the first pixel data.

In some embodiments, determining, by the mobile computing device, thefirst pixel score based on at least the first band-pass filter resultincludes determining the first pixel score based on the first band-passfilter result and a saturation value of the first pixel data.

In some embodiments, determining, by the mobile computing device, thefirst pixel score based on at least the first band-pass filter resultincludes determining the first pixel score based on the first band-passfilter result and a brightness value of the first pixel data.

In some embodiments, determining, by the mobile computing device, thefirst pixel score based on at least the first band-pass filter resultincludes determining the first pixel score based on the first band-passfilter result, a saturation value of the first pixel data, and abrightness value of the first pixel data.

In some embodiments, the method includes converting the first pixel datafrom an RGB domain to an HSB, HSV, or HSL domain.

In some embodiments, the method includes identifying, by the mobilecomputing device, the first pixel as associated with an LED of the oneor more LEDs in the image if the pixel score exceeds a threshold.

In some embodiments, the method includes identifying, by the mobilecomputing device, the first pixel as associated with an LED of the oneor more LEDs in the image based on an adjacent pixel score associatedwith an adjacent pixel adjacent to the first pixel in the image.

In another aspect, there is a computer program product, tangiblyembodied in a non-transitory computer readable storage medium, includinginstructions being operable to cause a mobile computing device to:acquire an image of a scene including one or more markers associatedwith IT equipment; apply a band-pass filter to first pixel dataassociated with a first pixel in the image to generate a first band-passfilter result, wherein a pass-band of the band-pass filter is based onthe light emitted by the one or more markers; determine a first pixelscore based on at least the first band-pass filter result; and store ina map first indicia of the first pixel score at a first map locationcorresponding to a first image location of the first pixel in the image.

In some embodiments, the computer program product includes instructionsbeing operable to cause a mobile computing device to apply the band-passfilter to second pixel data associated with a second pixel in the imageto generate a second band-pass filter result; determine a second pixelscore based on at least the second band-pass filter result; and store inthe map second indicia of the second pixel score at a second maplocation corresponding to a second image location of the second pixel inthe image.

In some embodiments, the computer program product includes instructionsbeing operable to cause a mobile computing device to apply the band-passfilter to a hue value of the first pixel data.

In some embodiments, the instructions to determine a first pixel scorebased on at least the first band-pass filter result include instructionsto determine the first pixel score based on the first band-pass filterresult and a saturation value of the first pixel data.

In some embodiments, the instructions to determine a first pixel scorebased on at least the first band-pass filter result include instructionsto determine the first pixel score based on the first band-pass filterresult and a brightness value of the first pixel data.

In some embodiments, the instructions to determine a first pixel scorebased on at least the first band-pass filter result include instructionsto determine the first pixel score based on the first band-pass filterresult, a saturation value of the first pixel data, and a brightnessvalue of the first pixel data.

In some embodiments, the computer program product includes instructionsbeing operable to cause a mobile computing device to convert the firstpixel data from an RGB domain to an HSB, HSV or HSL domain.

In some embodiments, the computer program product includes instructionsbeing operable to cause a mobile computing device to identify the firstpixel as associated with an LED of the one or more LEDs in the image ifthe pixel score exceeds a threshold.

In some embodiments, the computer program product includes instructionsbeing operable to cause a mobile computing device to identify the firstpixel as associated with an LED of the one or more LEDs in the imagebased on an adjacent pixel score associated with an adjacent pixeladjacent to the first pixel in the image.

In another aspect, there is a method executed on a mobile computingdevice for locating one or more light emitting diodes (LEDs) associatedwith one or more IT components. The method can include acquiring, by themobile computing device, an image of a scene including the one or moreLEDs, wherein the image has dimensions of N by M pixels. The method caninclude, for each pixel in the image: applying, by the mobile computingdevice, a band-pass filter to pixel data associated with the pixel togenerate a band-pass filter result, wherein a pass-band of the band-passfilter is based on the light emitted by the one or more LEDs;determining, by the mobile computing device, a pixel score based on atleast the band-pass filter result; and creating, by the mobile computingdevice, a map having dimensions N by M including indicia of the pixelscore for each pixel at a map location corresponding to an imagelocation of the pixel in the image.

In some embodiments, the first pixel score is the first band-pass filterresult. In some embodiments, the first pixel data are in an HSB, HSV, orHSL domain. In some embodiments, the one or more markers comprise one ormore light emitting diodes (LEDs).

Other aspects and advantages of the present technology will becomeapparent from the following detailed description, taken in conjunctionwith the accompanying drawings, illustrating the principles of theinvention by way of example only.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, features, and advantages of the presenttechnology, as well as the invention itself, will be more fullyunderstood from the following description of various embodiments, whenread together with the accompanying drawings, in which:

FIG. 1A depicts a rack including IT components;

FIG. 1B depicts a rack including IT components;

FIG. 2A depicts a front view of a mobile computing device;

FIG. 2B depicts a back view of a mobile computing device;

FIG. 2C depicts a block diagram of an analysis module of mobilecomputing device;

FIG. 3 depicts a flow chart for a method of locating one or more markersassociated with IT components in an image;

FIG. 4 illustrates an image; and

FIG. 5 illustrates a map.

DETAILED DESCRIPTION

In some applications, such as data center management applications oraugmented reality applications, it can be beneficial to locate an ITcomponent in an image. In some applications, a mobile computing devicecan be used to take an image of multiple IT components (e.g., multipleservers in a rack). It can be beneficial for the mobile computing deviceto be able to locate the various IT components in the image. Forexample, locating an IT component in the image can be useful foridentifying the IT component or identifying the position and/ororientation of the IT component in the image. The technology describedherein can be used to facilitate locating an IT component in an imagebased on markers (e.g., markers having known color and/or brightnessproperties) associated with the IT equipment. For example, an ITcomponent can include one or more markers on its face, such as lightemitting diodes (LEDs), florescent markers, etc. In some instances, thenumber of markers, arrangement of markers, or characteristics of lightemitted by the markers can be unique to the particular IT component, themodel of the IT component, or the brand of the IT component. Knowledgeof the number of markers, arrangement of markers, and/or characteristicsof light emitted by the markets on a particular IT component can be usedto identify that IT component. For example, a particular IT componentcan be identified in an image of a rack containing multiple ITcomponents based on the particular IT component's arrangement of markersand/or characteristics of the light emitted by the markers. As anotherexample, the position and orientation of an IT component in an image canbe determined based on how the markers appear in the image. Accordingly,being able to locate and identify the markers associated with ITcomponents in an image can be useful for these and other applications.

Described herein is technology for identifying markers associated withIT equipment in an image. In some embodiments, the technology cananalyze the pixels of an image to identify the location of one or moremarkers within the image (e.g., identify one or more pixels that likelyare a part of the image of the marker). The technology described canleverage known characteristics of the light emitted by the markers toidentify the markers in an image. In some embodiments, the technologyinvolves applying a band-pass filter to each pixel in an image todetermine if the pixel has characteristics associated with a marker. Forexample, the band-pass filter can have a pass-band approximatelycentered around the wavelength of the light emitted by the markers. Insome embodiments where different markers can emit different wavelengthsof light, multiple band-pass filters can be used. Using the band-passfilter, the technology can identify pixels with color that approximatelymatches the known wavelength of light emitted by the markers, andidentify pixels that are likely associated with a marker (e.g., thepixel is part of the image of the marker). In some embodiments, thetechnology involves analyzing multiple characteristics of the pixel inorder to determine whether the pixel is likely associated with a marker,as will be described in greater detail below. In some embodiments, thetechnology involves determining a pixel score for each pixel in theimage. The pixel score can be used to determine which pixels areassociated with markers (e.g., pixel scores above a threshold can beidentified as associated with markers). In some embodiments, neighboringpixels can be analyzed and grouped as associated with the same marker.

In some embodiments, the technology can generate a map of pixel scores.The pixel score map can have the same dimensions as the original image,such that each pixel in the image has a corresponding location in thepixel score map. Beneficially, the pixel score map can facilitatequickly locating a marker in the original image. For example, anaugmented reality application can determine the coordinates of a groupof high-score pixels in the map and use those coordinates to find thecorresponding marker in the image.

FIG. 1A depicts rack 105 including IT components. As illustrated, rack105 contains disk enclosures 110. Disk enclosures 110 contain hard disks120. Disk enclosures 110 and/or hard disks 120 include LEDs 130. FIG. 1Bdepicts rack 145 including IT components. As illustrated, rack 145contains disk enclosure 110 and servers 150, 155, 160, and 165. Servers150, 155, 160, and 165 include LEDs 130.

As illustrated in FIGS. 1A and 1B, each of disk enclosures 110 andservers 150, 155, 160, and 165, has one or more LEDs 130 arranged on itsface. As discussed above, the arrangement of LEDs 130 can be used toidentify the type of IT equipment in an image (e.g., distinguish betweendisk enclosures 110 and servers 150, 155, 160, and 165 based on thearrangement of LEDs 130). In some applications, the arrangement of LEDs130 can be used to determine the position of IT equipment in an image(e.g., determine the position of disk enclosures 110 based on thelocation and arrangement of LEDs 130 associated with disk enclosure110).

FIG. 2A depicts a front view of mobile computing device 200. As shown inFIG. 2A, mobile computing device 200 can have a bar-type body. In someembodiments, a mobile computing device can be a smartphone, cellularphone, tablet computer, laptop computer, or other computing device thatcan be brought into a data center. Mobile computing device 200 caninclude display 205, audio output unit 210, camera 215, and user inputunit 217. In some embodiments, display 205 can be touch sensitive (e.g.,a user can provide input to mobile computing device by touching display205).

FIG. 2B depicts a back view of mobile computing device 200. As shown inFIG. 2B, mobile computing device 200 can include camera 220. Camera 220can have a photographing direction that is substantially opposite to aphotographing direction of camera 215 and can have pixels differing frompixels of camera 215. Mobile computing device 200 can include flash 225adjacent to the camera 220. Flash 225 can emit light toward a subject incase of photographing the subject using camera 220. Mobile computingdevice 200 can include antenna 230 for communication.

FIG. 2C depicts a block diagram of analysis module 240 of mobilecomputing device 200. Camera 220 can produce original image 245.Original image 245 can be a digital image. In some embodiments, eachpixel of the image can have associated pixel data. The pixel data can berepresented in the Hue, Saturation, and Value (HSV) representation, Hue,Saturation, and Brightness (HSB) representation, and/or Hue, Saturation,and Lightness (HSL) representation.

Band-pass filter logic 250 can include logic that can be used to applyband-pass filtering to one or more pixels in original image 245, toproduce band-pass filter result 255. In some embodiments, the band-passfilter applied by band-pass filter logic 250 can be a band-pass filterfor a wavelength of light (e.g., passes wavelengths of light within thepass-band and rejects wavelengths of light outside the pass-band). Insome embodiments, one or more band-pass filters can be applied byband-pass filter logic 250, where each band-pass filter can be for awavelength of light associated with a particular type of marker (e.g., aband-pass filter for light emitted by green LEDs and a band-pass filterfor the light emitted by blue LEDs). Band-pass filter result 255 can bethe output of band-pass filter logic 250. In some embodiments, theoutput of the band-pass filter applied by band-pass filter logic 250 canbe numeric values that fall within a range (e.g., [0,1]) where pixelswith color that falls within the pass-band result in output of numericvalues in the high end of the range and pixels with color that fallsoutside the pass-band result in output of numeric values in the low endof the range. In some embodiments, the output of the band-pass filterapplied by band-pass filter logic 250 can fall off exponentially withthe magnitude of the difference between the color of the pixel and thepass band. In some embodiments, band-pass filter logic 250 can clipsmall values (e.g., output 0). In some embodiments, the output of theband-pass filter applied by band-pass filter logic 250 can be binaryvalues, where pixels with color that falls within the pass-band resultin output of a first value (e.g., 1) and pixels with color that fallsoutside the pass-band result in a second value (e.g., 0).

For example, in embodiments where original image 245 is in HSV, HSB, orHSL, the band-pass filter applied by band-pass filter logic 250 can be aband-pass filter for a particular Hue value or range of Hue values. Insome embodiments, the particular Hue value can be the expected Hue ofthe light emitted by an LED on an IT component. Accordingly, applicationof the band pass filter can identify pixels in the image likelyassociated with an LED.

Pixel score logic 260 can determine pixel score 265 for a pixel based,in part, on band-pass filter result 255. In some embodiments, pixelscore 265 can be band-pass filter result 255. In some embodiments, pixelscore logic 260 can determine pixel score 265 based on band-pass filterresult 255 and other attributes of the pixel being analyzed and/or otherpixels from the image. Pixel score logic 260 can determine pixel score265 based on band-pass filter result 255 and the saturation, brightness,value, and/or lightness of the pixel.

For example, in embodiments where original image 245 is in HSV, HSB, orHSL, pixel score logic 260 can determine pixel score 265 based onband-pass filter result 255 in combination with Saturation and/or Value,Saturation and/or Brightness, or Saturation and/or Lightness of thepixel. In some embodiments, pixel score 265 can be the sum or product ofthe band-pass filter result 255 and the Saturation and/or Value,Saturation and/or Brightness, or Saturation and/or Lightness of thepixel.

In some embodiments, pixel score logic 260 can determine pixel score 265based on pixels that neighbor the pixel being analyzed. For example, ifa pixel is surrounded by neighboring pixels with high pixel scores,pixel score 265 for the pixel being analyzed can be increased.

Map logic 270 can generate map 275 based pixel score 265. In someembodiments, map logic 270 can generate map 275 based on pixel scores265 for each pixel of original image 245. For example, map 275 can be a2 dimensional array of pixel scores 265. As another example, map 275 canbe a gray scale image having the same dimensions as original image 245,where the appearance of each pixel of map 275 is based on pixel score265 for the pixel at the corresponding location in original image 245(e.g., highest pixel scores appear white and lowest pixel scores appearblack). As another example, map 275 can include indicia of the pixelscore along with indicia of the band-pass filter passed by the pixel(e.g., whether the pixel passed a band-pass filter for light emitted bya green LED or a blue LED). More generally, map 275 can be anycollection of pixel scores that can be correlated to the pixels inoriginal image 245.

FIG. 3 depicts flow chart 300 for a method of locating one or moremarkers associated with IT components in an image. In some embodiments,the illustrated method can be executed by mobile computing device 200.In some embodiments, the method can be executed multiple times, whereeach time a different band-pass filter is applied (e.g., applying aband-pass filter for the light emitted by a green LED and applying aband-pass filter for the light emitted by a blue LED) to generatemultiple maps. At step 305, an image of a scene including one or moremarkers is acquired. In some embodiments, the image can be made up ofpixels, each represented by pixel data. The pixel data can be in theHue, Saturation, and Value (HSV) representation, Hue, Saturation, andBrightness (HSB) representation, and/or Hue, Saturation, and Lightness(HSL) representation. In some embodiments, the pixel data can be in theRGB representation and converted to HSV, HSB, or HSL. For example,camera 220 of mobile computing device 200 can acquire original image245.

At step 310, a band-pass filter is applied to pixel data associated witha pixel in the image to generate a band-pass filter result. In someembodiments, the band-pass filter can be for a wavelength of lightassociated with the light emitted by the markers (e.g., passes orselects wavelengths of light within a pass-band centered around thelight emitted by the markers and rejects wavelengths of light outsidethe pass-band). For example, band-pass filter logic 250 can apply aband-pass filter centered around a particular Hue to generate band-passfilter result 255. In some embodiments, one or more band-pass filterscan be applied by band-pass filter logic 250 (e.g., a band-pass filterfor light emitted by green LEDs and a band-pass filter for the lightemitted by blue LEDs).

At step 315, a pixel score is determined based on at least the band-passfilter result. For example, pixel score logic 260 can determine pixelscore 265 for a pixel based, in part, on band-pass filter result 255.Pixel score logic 260 can determine pixel score 265 based on band-passfilter result 255 and other attributes of the pixel being analyzedand/or other pixels from the image, such as the saturation, brightness,and/or lightness value of the pixel. Pixel score logic 260 can determinepixel score 265 based on pixels that neighbor the pixel being analyzed.

At step 320, indicia of the pixel score is stored in a map at a maplocation corresponding to an image location of the pixel in the image.For example, map logic 270 can store pixel score 265 in map 275. Pixelscore 265 can be stored to map 275 at a location corresponding to thelocation of the pixel in the image.

At step 325, it is determined whether there are additional pixels in theimage. If there are additional pixels in the image to analyze, themethod performs steps 310, 315, and 320 for the each of the remainingpixels.

With reference to FIGS. 4 and 5, an exemplary correspondence between animage (e.g., original image 245) and an associated map (e.g., map 275)is illustrated. FIG. 4 illustrates image 405. FIG. 5 illustrates map505. Image 405 can be analyzed as described herein to produce map 505.As illustrated, image 405 includes multiple IT components and LEDs 410.Map 505 includes indicia 510 corresponding to LEDs 410. As illustrated,each of indicia 510 corresponds to an LED 410. Beneficially, map 505isolates the location of LEDs 410 in image 405.

As described above, in some embodiments, the technology can be used toidentify IT components. An IT component can be identified by finding aknown configuration of markers for an IT component that approximatelymatches the map generated (e.g., map 275). In some embodiments, thetechnology can include applying multiple band-pass filters based on theknown configuration of markers for an IT component. For example, a diskenclosure with multiple hard drives can be known to have a row of greenLEDs (e.g., LEDs on the hard disks) and a blue LED located above the rowof green LEDs (e.g., disk enclosure 110). The technology can locate asimilar row of green LEDs in an image (e.g., by applying a band-passfilter for the light emitted by the green LEDs). To increase confidencethat the row of green LEDs found in the image is associated with a diskenclosure, the technology can then apply a band-pass filter for blueLEDs to determine if a blue LED appears in the image at the locationwhere the disk enclosure's blue LED is expected to be.

The above-described techniques can be implemented in digital electroniccircuitry, or in computer hardware, firmware, software, or incombinations of them. The implementation can be as a computer programproduct, i.e., a computer program tangibly embodied in an informationcarrier, e.g., in a machine-readable storage device, for execution by,or to control the operation of, data processing apparatus, e.g., aprogrammable processor, a computer, or multiple computers. A computerprogram can be written in any form of programming language, includingcompiled or interpreted languages, and it can be deployed in any form,including as a stand-alone program or as a module, component,subroutine, or other unit suitable for use in a computing environment. Acomputer program can be deployed to be executed on one computer or onmultiple computers at one site or distributed across multiple sites andinterconnected by a communication network.

Method steps can be performed by one or more programmable processorsexecuting a computer program to perform functions of the invention byoperating on input data and generating output. Method steps can also beperformed by, and apparatus can be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application-specific integrated circuit). Modules can refer to portionsof the computer program and/or the processor/special circuitry thatimplements that functionality.

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital computer. Generally, aprocessor receives instructions and data from a read-only memory or arandom access memory or both. The essential elements of a computer are aprocessor for executing instructions and one or more memory devices forstoring instructions and data. Generally, a computer also includes, orbe operatively coupled to receive data from or transfer data to, orboth, one or more mass storage devices for storing data, e.g., magnetic,magneto-optical disks, or optical disks. Data transmission andinstructions can also occur over a communications network. Informationcarriers suitable for embodying computer program instructions and datainclude all forms of non-volatile memory, including by way of examplesemiconductor memory devices, e.g., EPROM, EEPROM, and flash memorydevices; magnetic disks, e.g., internal hard disks or removable disks;magneto-optical disks; and CD-ROM and DVD-ROM disks. The processor andthe memory can be supplemented by, or incorporated in special purposelogic circuitry.

To provide for interaction with a user, the above described techniquescan be implemented on a computer having a display device, e.g., a CRT(cathode ray tube) or LCD (liquid crystal display) monitor, fordisplaying information to the user and a keyboard and a pointing device,e.g., a mouse or a trackball, by which the user can provide input to thecomputer (e.g., interact with a user interface element). Other kinds ofdevices can be used to provide for interaction with a user as well; forexample, feedback provided to the user can be any form of sensoryfeedback, e.g., visual feedback, auditory feedback, or tactile feedback;and input from the user can be received in any form, including acoustic,speech, or tactile input.

The above described techniques can be implemented in a distributedcomputing system that includes a back-end component, e.g., as a dataserver, and/or a middleware component, e.g., an application server,and/or a front-end component, e.g., a client computer having a graphicaluser interface and/or a Web browser through which a user can interactwith an example implementation, or any combination of such back-end,middleware, or front-end components. The components of the system can beinterconnected by any form or medium of digital data communication,e.g., a communication network. Examples of communication networksinclude a local area network (“LAN”) and a wide area network (“WAN”),e.g., the Internet, and include both wired and wireless networks.

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other.

The invention has been described in terms of particular embodiments. Thealternatives described herein are examples for illustration only and notto limit the alternatives in any way. The steps of the invention can beperformed in a different order and still achieve desirable results.Other embodiments are within the scope of the following claims.

What is claimed is:
 1. A method executed on a mobile computing devicefor locating one or more markers associated with IT equipmentcomprising: acquiring, by the mobile computing device, an image of ascene including the one or more markers; applying, by the mobilecomputing device, a band-pass filter to first pixel data associated witha first pixel in the image to generate a first band-pass filter result,wherein a pass-band of the band-pass filter is based on the lightemitted by the one or more markers; determining, by the mobile computingdevice, a first pixel score based on at least the first band-pass filterresult; storing, by the mobile computing device, in a map first indiciaof the first pixel score at a first map location corresponding to afirst image location of the first pixel in the image.
 2. The method ofclaim 1, further comprising: applying, by the mobile computing device,the band-pass filter to second pixel data associated with a second pixelin the image to generate a second band-pass filter result; determining,by the mobile computing device, a second pixel score based on at leastthe second band-pass filter result; storing, by the mobile computingdevice, in the map second indicia of the second pixel score at a secondmap location corresponding to a second image location of the secondpixel in the image.
 3. The method of claim 1, wherein the first pixelscore is the first band-pass filter result.
 4. The method of claim 1,wherein the first pixel data are in an HSB, HSV or HSL domain.
 5. Themethod of claim 4, further comprising applying the band-pass filter to ahue value of the first pixel data.
 6. The method of claim 4, whereindetermining, by the mobile computing device, the first pixel score basedon at least the first band-pass filter result comprises determining thefirst pixel score based on the first band-pass filter result and asaturation value of the first pixel data.
 7. The method of claim 4,wherein determining, by the mobile computing device, the first pixelscore based on at least the first band-pass filter result comprisesdetermining the first pixel score based on the first band-pass filterresult and a brightness value of the first pixel data.
 8. The method ofclaim 4, wherein determining, by the mobile computing device, the firstpixel score based on at least the first band-pass filter resultcomprises determining the first pixel score based on the first band-passfilter result, a saturation value of the first pixel data, and abrightness value of the first pixel data.
 9. The method of claim 1,further comprising converting the first pixel data from an RGB domain toan HSB, HSV or HSL domain.
 10. The method of claim 1, wherein the one ormore markers comprise one or more light emitting diodes (LEDs).
 11. Themethod of claim 10, further comprising: identifying, by the mobilecomputing device, the first pixel as associated with an LED of the oneor more LEDs in the image if the pixel score exceeds a threshold. 12.The method of claim 10, further comprising: identifying, by the mobilecomputing device, the first pixel as associated with an LED of the oneor more LEDs in the image based on an adjacent pixel score associatedwith an adjacent pixel adjacent to the first pixel in the image.
 13. Acomputer program product, tangibly embodied in a non-transitory computerreadable storage medium, comprising instructions being operable to causea mobile computing device to: acquire an image of a scene including oneor more markers associated with IT equipment; apply a band-pass filterto first pixel data associated with a first pixel in the image togenerate a first band-pass filter result, wherein a pass-band of theband-pass filter is based on the light emitted by the one or moremarkers; determine a first pixel score based on at least the firstband-pass filter result; store in a map first indicia of the first pixelscore at a first map location corresponding to a first image location ofthe first pixel in the image.
 14. The computer program product of claim13, further comprising instructions being operable to cause a mobilecomputing device to: apply the band-pass filter to second pixel dataassociated with a second pixel in the image to generate a secondband-pass filter result; determine a second pixel score based on atleast the second band-pass filter result; store in the map secondindicia of the second pixel score at a second map location correspondingto a second image location of the second pixel in the image.
 15. Thecomputer program product of claim 13, wherein the first pixel score isthe first band-pass filter result.
 16. The computer program product ofclaim 13, wherein the first pixel data are in an HSB, HSV or HSL domain.17. The computer program product of claim 13, further comprisinginstructions being operable to cause a mobile computing device to applythe band-pass filter to a hue value of the first pixel data.
 18. Thecomputer program product of claim 13, wherein the instructions todetermine a first pixel score based on at least the first band-passfilter result comprise instructions to determine the first pixel scorebased on the first band-pass filter result and a saturation value of thefirst pixel data.
 19. The computer program product of claim 13, whereinthe instructions to determine a first pixel score based on at least thefirst band-pass filter result comprise instructions to determine thefirst pixel score based on the first band-pass filter result and abrightness value of the first pixel data.
 20. The computer programproduct of claim 13, wherein the instructions to determine a first pixelscore based on at least the first band-pass filter result compriseinstructions to determine the first pixel score based on the firstband-pass filter result, a saturation value of the first pixel data, anda brightness value of the first pixel data.
 21. The computer programproduct of claim 13, further comprising instructions being operable tocause a mobile computing device to convert the first pixel data from anRGB domain to an HSB or HSL domain.
 22. The computer program product ofclaim 13, wherein the one or more markers comprise one or more lightemitting diodes (LEDs).
 23. The computer program product of claim 22,further comprising instructions being operable to cause a mobilecomputing device to: identify the first pixel as associated with an LEDof the one or more LEDs in the image if the pixel score exceeds athreshold.
 24. The computer program product of claim 22, furthercomprising instructions being operable to cause a mobile computingdevice to: identify the first pixel as associated with an LED of the oneor more LEDs in the image based on an adjacent pixel score associatedwith an adjacent pixel adjacent to the first pixel in the image.
 25. Amethod executed on a mobile computing device for locating one or morelight emitting diodes (LEDs) associated with one or more IT componentscomprising: acquiring, by the mobile computing device, an image of ascene including the one or more LEDs, wherein the image has dimensionsof N by M pixels; for each pixel in the image: applying, by the mobilecomputing device, a band-pass filter to pixel data associated with thepixel to generate a band-pass filter result, wherein a pass-band of theband-pass filter is based on the light emitted by the one or more LEDs;determining, by the mobile computing device, a pixel score based on atleast the band-pass filter result; creating, by the mobile computingdevice, a map having dimensions N by M comprising indicia of the pixelscore for each pixel at a map location corresponding to an imagelocation of the pixel in the image.